Issue 22, 2024

Development of a highly sensitive ampicillin sensor utilizing functionalized aptamers

Abstract

To develop a sensitive and simple ampicillin (AMP) sensor for trace antibiotic residue detection, the influencing factors of the modification effect of nanogold-functionalized nucleic acid sequences (Adenine: A, Thymine: T) were comprehensively analyzed in this study, including the modification method, base length and type. It was found that under the same base concentration, longer chains are more likely to reach saturation than shorter chains; and when the base concentration and length are both the same, A exhibits a higher saturation modification level compared to T. Based on these research findings, a highly sensitive fluorescence aptamer sensor for detecting ampicillin was constructed using the optimized functionalized sequence (ployA6-aptamer) and experimental conditions (6 hours binding time between nucleic acid aptamer and complementary strand, pH 7 working solution, 20 minutes detection time) based on the principle of fluorescence resonance energy transfer. The sensor has a detection range of 0.18 ng ml−1 to 3.11 ng ml−1 for ampicillin, with a detection limit of 0.04 ng ml−1. It exhibits significant selectivity and achieves an average recovery rate of 98.71% in tap water and 91.83% in milk. This method can be used not only for residual ampicillin detection, but also for highly sensitive detection of various antibiotics and small biological molecules by replacing the aptamer type. It provides a research basis for the design of highly sensitive fluorescence aptamer sensors and further applications of nanogold@DNA composite structures.

Graphical abstract: Development of a highly sensitive ampicillin sensor utilizing functionalized aptamers

Supplementary files

Article information

Article type
Paper
Submitted
19 Jan 2024
Accepted
25 Apr 2024
First published
22 May 2024

Anal. Methods, 2024,16, 3522-3529

Development of a highly sensitive ampicillin sensor utilizing functionalized aptamers

L. Ren, S. Ma, C. Li, D. Wang, P. Zhang, L. Wang, Z. Qin and L. Jiang, Anal. Methods, 2024, 16, 3522 DOI: 10.1039/D4AY00130C

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